Our Opportunity:

Advertising is a critical component of the ecommerce ecosystem and provides a critical revenue stream to the company.  At Chewy, Sponsored Ads team is looking for Data Engineer II to help with integrating and processing data from various streams to influence product strategy, data science research and machine learning strategy, business and analytical teams strategy.  

As a Data Engineer in the Sponsored Advertising team, youll be part of core technical team and will create data-pipelines across the breadth of Chewy systems to enable insights across Pet-parents engagement, customer experience, advertiser experience, product and catalog systems, inventory systems, campaign management systems, bidding and pricing data, analytics data-lake. Youll be creating pipelines that process high scale streaming data as well as batch-data to implement data-strategy for ads. Youll be at forefront of driving technology driven business impact. You will work closely with analytics and product management teams to assess various experiment research before launch, work with machine learning engineers to enable innovative features integration, work with software engineers to implement state of art algorithms and work with ads-leadership to identify and assess various business opportunities.

Sponsored Ads creates a win-win ecosystem for shoppers, brand owners and Chewy! Shoppers (pet Parents) are offered a range of alternate options to help them choose better and learn about new products, new brands, new promotions, and different price points. Brand owners and advertisers get to showcase their product offerings in the front row for their target audience (proud pet owners) and maximize their reach.

Come be part of the Sponsored Ads teams impactful journey at Chewy!

What You'll Do:

• Design and Optimize Data Systems: Develop, optimize, and maintain data architecture and pipelines using advanced design and programming patterns, adhering to best practices.
• Data Integration and Management: Manage and enhance our SSOT tables and data marts critical for daily business decisions.
• Collaborative Leadership: Act as a trusted advisor to analytics teams and business partners, product managers, data-scientists and MLEs thereby providing expert consultation and communicating sophisticated data-driven insights.
• Mentorship: Mentor and coach peers on data standards and best practices, promoting a culture of continuous learning and improvement.
• Innovative Solutions: Lead the evaluation and deployment of cutting-edge tools and processes for data engineering to boost overall organizational productivity.
• Strategic Partnerships: Collaborate with leaders, vendors, and data practitioners across Chewy to develop technical architectures for strategic projects and initiatives.
• Documentation and Agile Practices: Document technical details of work and adhere to agile methodologies, utilizing tools such as Jira and Confluence.

What You'll Need:

• Education: Bachelors or Masters degree in Computer Science, Engineering, Information Systems, Mathematics, or a related field.
• Professional Experience: At least 3 years of experience in data engineering, with a strong focus on data integration and pipeline construction in cloud environments and enterprise data warehouses like Snowflake.
• Technical Proficiency: Expertise in SQL and programming languages such as Python; familiarity with big data technologies like Apache Hadoop, Spark, and Kafka.
• Leadership and Communication: Demonstrated ability to lead projects and communicate effectively with stakeholders at all levels.
• Innovative and Analytical Mindset: Strong problem-solving skills and the ability to adapt to new technologies and changing business requirements.

Bonus:

• Advanced Programming: Strong proficiency in Python.
• Industry Experience: Prior experience in related domains like digital advertising, sponsored products or display ads in e-commerce, retail, or startup environments.
• Certifications: AWS Developer or Data Analytics certifications.
• BI and Analytics Tools: Experience with BI tools such as Tableau, Power BI, or similar.